{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T16:14:05Z","timestamp":1761581645441},"reference-count":15,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Wavelets Multiresolut Inf. Process."],"published-print":{"date-parts":[[2018,3]]},"abstract":"<jats:p> With the wide applications of face recognition techniques, spoofing detection is playing an important role in the security systems and has drawn much attention. This research presents a multispectral face anti-spoofing method working with both visible (VIS) and near-infrared (NIR) spectra imaging, which exploits VIS\u2013NIR image consistency for spoofing detection. First, we use part-based methods to extract illumination robust local descriptors, and then the consistency is calculated to perform spoofing detection. In order to further exploit multispectral correlation in local patches and to be free from manually chosen regions, we learn a confidence factor map for all the patches, which is used in final classifier. Experimental results of self-collected datasets, public Msspoof and PolyU-HSFD datasets show that the proposed approach gains promising results for both intra-dataset and cross-dataset testing scenarios, and that our method can deal with different illumination and both photo and screen spoofing. <\/jats:p>","DOI":"10.1142\/s0219691318400039","type":"journal-article","created":{"date-parts":[[2018,1,4]],"date-time":"2018-01-04T09:22:32Z","timestamp":1515057752000},"page":"1840003","source":"Crossref","is-referenced-by-count":15,"title":["Multispectral face spoofing detection using VIS\u2013NIR imaging correlation"],"prefix":"10.1142","volume":"16","author":[{"given":"Xudong","family":"Sun","sequence":"first","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Zhongguancun East Road, Haidian District, Beijing 100190, P. R. China"},{"name":"School of Computer and Control Engineering, University of Chinese Academy of Sciences, Zhongguancun East Road, Haidian District, Beijing 100190, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Zhongguancun East Road, Haidian District, Beijing 100190, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changping","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Zhongguancun East Road, Haidian District, Beijing 100190, P. R. 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